Plant disease detection and Solution using Image Classification

An automated plant disease detection, Progressive Web App that will help the farmers to detect the disease in their crops and will also give insights on its treatment .

Auto Chloro is a plant disease classifier & remedies provider that uses deep learning. It can predict diseases and provide remedies. The GUI is based on Bangla Language keeping in mind that, our primary target is to create an application to predict plant diseases and provide remedies for the Bangladeshi people.

This project uses CNN to identify diseases in plants using image of their images of leaves

Agri-Pal is the simplest solution to aid a farmer in Agriculture - Crop and Poultry Farming. Agri-Pal is a simple Plug n Play device ensuring Disease Detection and Animal Breach Detection.

[Archive] Please see below URL

A tool to scan crops and predict healthy crops, crop rust, or powdery mildews.

Farmer assistant system VCET Hackathon 2k22

This repository contains code and resources for an end-to-end system designed to automate the detection and severity estimation of diseases in tomato plants.

Detect the Disease in Crop and recommend pesticides for it.

🌾 An AI-powered Crop Disease Predictor Web App that uses advanced image recognition to identify crop diseases.

Flutter app which helps farmers take the right decisions with their crop regarding diseases. Our team's idea for GDSC solution challenge 2024

This repository as all the files of the HELPMATE webpage

METADATA-FARMER ASSISTANCE WEBAPP | AI & ML

This project leverages deep learning to identify crop diseases from images. Built with TensorFlow, the app allows users to upload crop images and predicts the disease. It features a user-friendly interface, feedback submission, and an informative "About" section. Perfect for early disease detection in crops.

A Keras Sequential Model which predicts crop diseases of 18 crops across 55 diseases; deployed on a flask based web app.

Crop disease detection website

The Smart Crop Disease Detection System is a Django web app that uses machine learning to identify crop diseases from leaf images. It helps farmers detect diseases quickly and take action to protect their crops. The system features AWS S3 image storage, TensorFlow Lite integration, and a responsive front-end for easy use.

This project leverages deep learning to identify crop diseases from images. Built with TensorFlow, the app allows users to upload crop images and predicts the disease. It features a user-friendly interface, feedback submission, and an informative "About" section. Perfect for early disease detection in crops.

Testing the Text to speech feature for a Crop disease treatmnet prediction app